{"total":14,"rows":[{"id":"2402.08567","title":"Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast","created":"2024-02-13","cited_by_count":153,"area":"mllm"},{"id":"2312.03777","title":"On the Robustness of Large Multimodal Models Against Image Adversarial Attacks","created":"2023-12-06","cited_by_count":92,"area":"mllm"},{"id":"2311.11261","title":"Adversarial Prompt Tuning for Vision-Language Models","created":"2023-11-19","cited_by_count":44,"area":"mllm"},{"id":"2406.05491","title":"One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models","created":"2024-06-08","cited_by_count":40,"area":"mllm"},{"id":"2410.23687","title":"Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey","created":"2024-10-31","cited_by_count":23,"area":"mllm"},{"id":"2605.26501","title":"Unveiling the Fragility of Vision-Language Models: Multi-Modal Adversarial Synergy via Texture-Constrained Perturbations and Cross-Modal Optimization","created":"2026-05-26","cited_by_count":9,"area":"mllm"},{"id":"2412.12722","title":"Defending LVLMs Against Vision Attacks through Partial-Perception Supervision","created":"2024-12-17","cited_by_count":7,"area":"mllm"},{"id":"2510.11096","title":"CoDefend: Cross-Modal Collaborative Defense via Diffusion Purification and Prompt Optimization","created":"2025-10-13","cited_by_count":2,"area":"mllm"},{"id":"2511.19257","title":"Medusa: Cross-Modal Transferable Adversarial Attacks on Multimodal Medical Retrieval-Augmented Generation","created":"2025-11-24","cited_by_count":2,"area":"mllm"},{"id":"2506.01064","title":"Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs","created":"2025-06-01","cited_by_count":1,"area":"mllm"},{"id":"2506.11472","title":"Toward Inherently Robust VLMs Against Visual Perception Attacks","created":"2025-06-13","cited_by_count":1,"area":"mllm"},{"id":"2606.06186","title":"Adversarial Attacks Already Tell the Answer: Directional Bias-Guided Test-time Defense for Vision-Language Models","created":"2026-06-04","cited_by_count":1,"area":"mllm"},{"id":"2605.16090","title":"A Cross-Modal Prompt Injection Attack against Large Vision-Language Models with Image-Only Perturbation","created":"2026-05-15","cited_by_count":0,"area":"mllm"},{"id":"2608.08815","title":"Distilling Vision-Language Models for Robust Traffic Sign Perception in Autonomous Vehicles","created":"2026-08-09","cited_by_count":0,"area":"mllm"}],"next_cursor":null}